Pymcr

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- Providing sklearn-like features
- Added fit_transform method that acts like the `sklearn NMF fit_transform
method <https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF.fit>`_.
- Returns C_
- Added components_ attribute, which is synonymous with ST_
- Added fit_kwargs parameter to McrAR that will pass forward to the fit and fit_transform methods
- One can, e.g., set the ST or C guess from instantiation instead of calling fit or fit_transform

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- Moved to Github actions for CD
- Logging setup by default upon importing the library.
- Updated Jupyter Notebooks to reflect the change to the logging setup
- Minor bug fixes

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- Moved to Github actions for CI

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- Jupyter Notebook in Examples from `JRes NIST publication <https://doi.org/10.6028/jres.124.018>`_.
- Minor tweeks and fixes
- Added Conda-Forge badge

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- Implemented logging and removed print() statements
- Removed Jupyter Notebook from forthcoming pub -- will return in the future with better examples
- Minor fixes to CI

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- Documentation: https://pages.nist.gov/pyMCR or build locally via Sphinx
- Added Jupyter Notebook that generates images from forthcoming publication.
- Perform semi-learning: assigning some input ST or C components to be static in fit method.
- Main class pymcr.mcr.McrAls renamed to pymcr.mcr.McrAR
- **Constraints**

- Non-negative cumulative summation
- Zero end-points
- Zero (approx) cumulative summation end-points (can specify nodes as well)
- Compress or cut values above or below a threshold value
- Replace sum-across-features samples (e.g., 0 concentration) with prescribed target
- Enforce a plane ("planarize"). E.g., a concentration image is a plane.